"# 附加阅读资料
#### （按名称排序）

- [【彻底解说】从现在开始工程师必备的技能，阅读「Prompt Engineering Guide」来整理思路](https://dev.classmethod.jp/articles/how-to-design-prompt-engineering/)
- [GPT-3 的即时工程的三个原则](https://www.linkedin.com/pulse/3-principles-prompt-engineering-gpt-3-ben-whately)
- [面向初学者的生成式语言模型指南 - LaMBDA 指南](https://aitestkitchen.withgoogle.com/how-lamda-works)
- [用于大型语言模型的 Prompt Engineering 全面介绍](https://www.mihaileric.com/posts/a-complete-introduction-to-prompt-engineering)
- [ChatGPT Prompt Engineering 的通用框架](https://medium.com/@thorbjoern.heise/a-generic-framework-for-chatgpt-prompt-engineering-7097f6513a0b)
- [优化 ChatGPT Prompt 的 SEO 指南](https://searchengineland.com/chatgpt-prompts-seo-393523)
- [AI 内容生成](https://www.jonstokes.com/p/ai-content-generation-part-1-machine)
- [AI 的兴起引发了新职称：Prompt 工程师](https://www.axios.com/2023/02/22/chatgpt-prompt-engineers-ai-job)
- [AI 安全，RLHF 和自监督 - Jared Kaplan | Stanford MLSys #79](https://www.youtube.com/watch?v=fqC3D-zNJUM&ab_channel=StanfordMLSysSeminars)
- [了不起的文本指令学习论文](https://github.com/RenzeLou/awesome-instruction-learning)
- [Awesome ChatGPT Prompts](https://github.com/f/awesome-chatgpt-prompts)
- [最佳 100+ 稳定 Diffusion Prompt](https://mpost.io/best-100-stable-diffusion-prompts-the-most-beautiful-ai-text-to-image-prompts)
- [使用 OpenAI API 进行 Prompt Engineering 的最佳实践](https://help.openai.com/en/articles/6654000-best-practices-for-prompt-engineering-with-openai-api)
- [构建 GPT-3 应用程序 - 超越提示](https://medium.com/data-science-at-microsoft/building-gpt-3-applications-beyond-the-prompt-504140835560)
- [AI 真的可以免受基于文本的攻击吗？](https://techcrunch.com/2023/02/24/can-language-models-really-be-protected-from-text-based-attacks/)"。- [ChatGPT, 人工智能和 GPT-3 应用和用例](https://gpt3demo.com)
- [ChatGPT 提示](https://twitter.com/aaditsh/status/1636398208648658945?s=20)
- [CMU 高级自然语言处理 2022：提示](https://youtube.com/watch?v=5ef83Wljm-M&feature=shares)
- [常识作为暗物质-崔烨进 | 斯坦福 MLSys＃78](https://youtube.com/live/n4HakBqoCVg?feature=shares)
- [用你的话创造图像-Bing Image Creator 来到了新 Bing](https://blogs.microsoft.com/blog/2023/03/21/create-images-with-your-words-bing-image-creator-comes-to-the-new-bing/)
- [Curtis64 的一系列提示 Gist](https://gist.github.com/Curtis-64)
- [DALL·E 2 提示工程指南](https://docs.google.com/document/d/11WlzjBT0xRpQhP9tFMtxzd0q6ANIdHPUBkMV-YB043U/edit#)
- [DALL·E 2 预览-风险和限制](https://github.com/openai/dalle-2-preview/blob/main/system-card.md)
- [DALLE 提示书](https://dallery.gallery/the-dalle-2-prompt-book)
- [DALL-E，再给我做一幅毕加索画吧](https://www.newyorker.com/magazine/2022/07/11/dall-e-make-me-another-picasso-please?)
- [扩散模型：实用指南](https://scale.com/guides/diffusion-models-guide)
- [利用 GPT-3 提示](https://twitter.com/goodside/status/1569128808308957185)
- [探索提示注入攻击](https://research.nccgroup.com/2022/12/05/exploring-prompt-injection-attacks)
- [将 GPT-3 的上下文学习推广到不自然的语言处理：好的、坏的和神秘的](http://ai.stanford.edu/blog/in-context-learning)
- [FVQA 2.0：将对抗样本引入基于事实的视觉问答](https://arxiv.org/pdf/2303.10699.pdf)
- [Cohere 的生成式人工智能：第1部分-模型提示](https://txt.cohere.ai/generative-ai-part-1)
- [生成式人工智能：斯坦福 HAI 的视角](https://hai.stanford.edu/sites/default/files/2023-03/Generative_AI_HAI_Perspectives.pdf)
- [看看这个新职位：“提示工程师”作为 AI 聊天机器人的心理学家](https://futurism.com/prompt-engineers-ai)。- [对 GPT-3 进行图灵测试](https://lacker.io/ai/2020/07/06/giving-gpt-3-a-turing-test.html)
- [GPT-3 及其后继品](https://youtube.com/watch?v=-lnHHWRCDGk)
- [GPT3 和提示：快速入门](https://buildspace.so/notes/intro-to-gpt3-prompts)
- [Bing 的新 ChatGPT 类功能实践](https://techcrunch.com/2023/02/08/hands-on-with-the-new-bing/)
- [如何画任何东西](https://andys.page/posts/how-to-draw)
- [如何获得好的图片](https://www.reddit.com/r/StableDiffusion/comments/x41n87/how_to_get_images_that_dont_suck_a)
- [如何让 LLM 说真话](https://evanjconrad.com/posts/world-models)
- [如何完善你的 AI 生成器提示写作](https://www.sydney.edu.au/news-opinion/news/2023/02/28/how-to-perfect-your-prompt-writing-for-ai-generators.html)
- [如何书写好的提示](https://andymatuschak.org/prompts)
- [如果我在 2023 年开始进行提示工程：我的 8 个内幕贴士](https://youtube.com/watch?v=SirW7feTjh0&feature=shares)
- [Bing Chat 上的间接提示注入](https://greshake.github.io/)
- [GPT-3 提示参数交互指南](https://sevazhidkov.com/interactive-guide-to-gpt-3-prompt-parameters)
- [通过人类反馈介绍强化学习](https://www.surgehq.ai/blog/introduction-to-reinforcement-learning-with-human-feedback-rlhf-series-part-1)
- [为提示工程正名](https://simonwillison.net/2023/Feb/21/in-defense-of-prompt-engineering/)
- [ChatGPT 的越狱：您需要了解的所有内容](https://metaroids.com/learn/jailbreaking-chatgpt-everything-you-need-to-know/)
- [语言模型和提示工程：NLP 提示方法的系统调查](https://youtube.com/watch?v=OsbUfL8w-mo&feature=shares)
- [语言模型行为：全面调查](https://arxiv.org/abs/2303.11504)
- [学习提示](https://learnprompting.org)
- [Meet Claude: Anthropic 的 ChatGPT 对手](https://scale.com/blog/chatgpt-vs-claude)- [提示式编程的方法](https://generative.ink/posts/methods-of-prompt-programming)
- [模式崩溃的奥秘](https://www.lesswrong.com/posts/t9svvNPNmFf5Qa3TA/mysteries-of-mode-collapse)
- [文本到图像生成器的 NLP：提示分析](https://heartbeat.comet.ml/nlp-for-text-to-image-generators-prompt-analysis-part-1-5076a44d8365)
- [Deep Learning CS224N/Ling284 自然语言处理 - 第 11 讲：提示、指令调整和 RLHF](http://web.stanford.edu/class/cs224n/slides/cs224n-2023-lecture11-prompting-rlhf.pdf)
- [Prompt Engineering 笔记，作者为 sw-yx](https://github.com/sw-yx/ai-notes)
- [OpenAI Cookbook](https://github.com/openai/openai-cookbook)
- [多个应用的 OpenAI 提示示例](https://platform.openai.com/examples)
- [预训练、提示和预测——NLP 的新范式](http://pretrain.nlpedia.ai)
- [Prompt Engineer：科技界最热门的职称？](https://www.peoplematters.in/article/talent-management/is-prompt-engineering-the-hottest-job-in-ai-today-37036)
- [Lilian Weng 的 Prompt Engineering 文章](https://lilianweng.github.io/posts/2023-03-15-prompt-engineering/)
- [Prompt Engineering 101 - 介绍和资源](https://www.linkedin.com/pulse/prompt-engineering-101-introduction-resources-amatriain)
- [Prompt Engineering 101：自动完成、零样本、一次样本和少量样本提示](https://youtube.com/watch?v=v2gD8BHOaX4&feature=shares)
- [Prompt Engineering 101](https://humanloop.com/blog/prompt-engineering-101)
- [Prompt Engineering - 一个新的职业？](https://www.youtube.com/watch?v=w102J3_9Bcs&ab_channel=PatrickDebois)
- [co:here 的 Prompt Engineering](https://docs.cohere.ai/docs/prompt-engineering)
- [Microsoft 的 Prompt Engineering](https://microsoft.github.io/prompt-engineering)
- [Prompt Engineering：未来的职业](https://shubhamsaboo111.medium.com/prompt-engineering-the-career-of-future-2fb93f90f117)
- [我们自己的文档上的 davinci-003 提示工程用于自动支持（第 I 部分）](https://www.patterns.app/blog/2022/12/21/finetune-llm-tech-support)。- [提示工程指南：如何设计完美提示](https://richardbatt.co.uk/prompt-engineering-guide-how-to-engineer-the-perfect-prompts)
- [GPT-3的提示工程](https://www.analyticsvidhya.com/blog/2022/05/prompt-engineering-in-gpt-3)
- [提示工程模板](https://docs.google.com/spreadsheets/d/1-snKDn38-KypoYCk9XLPg799bHcNFSBAVu2HVvFEAkA/edit#gid=0)
- [GitHub的提示工程主题](https://github.com/topics/prompt-engineering)
- [提示工程：2023年的终极指南[GPT-3和ChatGPT]](https://businessolution.org/prompt-engineering/)
- [从语言到艺术的提示工程](https://www.saxifrage.xyz/post/prompt-engineering)
- [使用OpenAI的GPT-3和其他LLM的提示工程](https://youtube.com/watch?v=BP9fi_0XTlw&feature=shares)
- [针对GPT-3的提示注入攻击](https://simonwillison.net/2022/Sep/12/prompt-injection)
- [读取OpenAI API密钥的提示注入](https://twitter.com/ludwig_stumpp/status/1619701277419794435?s=20&t=GtoMlmYCSt-UmvjqJVbBSA)
- [提示：使用语言模型进行NLP任务的更好方法](https://thegradient.pub/prompting/)
- [针对少样本学习的提示](https://www.cs.princeton.edu/courses/archive/fall22/cos597G/lectures/lec05.pdf)
- [NLP中的提示：基于提示的零样本学习](https://savasy-22028.medium.com/prompting-in-nlp-prompt-based-zero-shot-learning-3f34bfdb2b72)
- [使用语言模型的提示方法及其在弱监督中的应用](https://snorkel.ai/prompting-methods-with-language-models-nlp)
- [Gwern的编程提示](https://www.gwern.net/GPT-3#prompts-as-programming)
- [使用新的AI动力Bing的通信员提示](https://blogs.microsoft.com/blog/2023/03/16/prompts-for-communicators-using-the-new-ai-powered-bing/)
- [为了好玩而进行的反向提示工程（无盈利）](https://lspace.swyx.io/p/reverse-prompt-eng)
- [检索增强生成的多模态信息：一份综述](https://arxiv.org/pdf/2303.10868.pdf)- [你想成为一个Prompt工程师吗：未来的关键职业](https://venturebeat.com/ai/so-you-want-to-be-a-prompt-engineer-critical-careers-of-the-future/)
- [模拟器](https://www.lesswrong.com/posts/vJFdjigzmcXMhNTsx/simulators)
- [从指令开始](https://beta.openai.com/docs/quickstart/start-with-an-instruction)
- [与机器对话：Prompt工程和注入](https://artifact-research.com/artificial-intelligence/talking-to-machines-prompt-engineering-injection)
- [AI领域最热门的新工作：AI语言专家，无需编码](https://www.washingtonpost.com/technology/2023/02/25/prompt-engineers-techs-next-big-job/)
- [《Fed Honeypot》书籍](https://fedhoneypot.notion.site/25fdbdb69e9e44c6877d79e18336fe05?v=1d2bf4143680451986fd2836a04afbf4)
- [《ChatGPT Prompt Book》](https://docs.google.com/presentation/d/17b_ocq-GL5lhV_bYSShzUgxL02mtWDoiw9xEroJ5m3Q/edit#slide=id.gc6f83aa91_0_79)
- [《ChatGPT List of Lists》: 一个收集了3000多个提示、示例、用例、工具、API、扩展、失败和其他资源的汇总](https://medium.com/mlearning-ai/the-chatgpt-list-of-lists-a-collection-of-1500-useful-mind-blowing-and-strange-use-cases-8b14c35eb)
- [本世纪最重要的工作技能](https://www.theatlantic.com/technology/archive/2023/02/openai-text-models-google-search-engine-bard-chatbot-chatgpt-prompt-writing/672991/)
- [语言的镜子](https://deepfates.com/the-mirror-of-language)
- [瓦鲁易效应（超级文章）](https://www.lesswrong.com/posts/D7PumeYTDPfBTp3i7/the-waluigi-effect-mega-post)
- [Bing的AI辅助搜索的想法和印象](https://simonwillison.net/2023/Feb/24/impressions-of-bing/)
- [通过生成式AI释放创造力：学习如何构建创新产品！](https://youtube.com/watch?v=jqTkMpziGBU&feature=shares)
- [Prompt工程释放创造力](https://youtube.com/watch?v=PFsbWAC4_rk&feature=shares)- [使用GPT-Eliezer来对抗ChatGPT越狱](https://www.alignmentforum.org/posts/pNcFYZnPdXyL2RfgA/using-gpt-eliezer-against-chatgpt-jailbreaking)
- [ChatGPT在做什么...以及为什么它有效？](https://writings.stephenwolfram.com/2023/02/what-is-chatgpt-doing-and-why-does-it-work/)
- [为什么ChatGPT如此出色？](https://scale.com/blog/chatgpt-reinforcement-learning)